Distant Viewing Explorer
Developed by Lauren Tilton et all
Developed by Lauren Tilton et all
Developed by Lauren Tilton et all
Developed by Lauren Tilton et all
Django is a high-level Python web framework that enables rapid development of secure, scalable web applications—making it a powerful asset in digital humanities projects that involve content management, data visualization, and interactive storytelling. With built-in features like URL routing, database integration, templating, and user authentication, Django allows scholars to build custom platforms for archives, oral histories, exhibits, and multilingual sites. Its emphasis on readability, modularity, and extensibility makes it ideal for interdisciplinary teams aiming to publish complex, data-rich humanities research on the web.
Django is a high-level Python web framework that enables rapid development of secure, scalable web applications—making it a powerful asset in digital humanities projects that involve content management, data visualization, and interactive storytelling. With built-in features like URL routing, database integration, templating, and user authentication, Django allows scholars to build custom platforms for archives, oral histories, exhibits, and multilingual sites.
Python is a powerful, user-friendly programming language widely adopted in digital humanities for tasks ranging from data cleaning and text analysis to web scraping, visualization, and machine learning. Its readable syntax and rich ecosystem of libraries—such as Pandas for structured data, NLTK for natural language processing, and Matplotlib for charting—make it ideal for humanities scholars working with large corpora, metadata, or networks. Whether building interactive exhibits or uncovering patterns in archival documents, Python offers a flexible toolkit for rigorous, reproducible, and creative research.
Python is a powerful, user-friendly programming language widely adopted in digital humanities for tasks ranging from data cleaning and text analysis to web scraping, visualization, and machine learning. Its readable syntax and rich ecosystem of libraries—such as Pandas for structured data, NLTK for natural language processing, and Matplotlib for charting—make it ideal for humanities scholars working with large corpora, metadata, or networks.